Mathematics: A Discrete Introduction
3rd Edition
ISBN: 9780840049421
Author: Edward A. Scheinerman
Publisher: Cengage Learning
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Chapter 2.12, Problem 12.30E
i.
To determine
To prove the given expression
ii.
To determine
To prove the given expression
iii.
To determine
To prove the given expression
iv.
To determine
To prove the given expression
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Chapter 2 Solutions
Mathematics: A Discrete Introduction
Ch. 2.8 - Write out all the possible two-letter words one...Ch. 2.8 - Airports have names, but they also have...Ch. 2.8 - Prob. 8.3ECh. 2.8 - Prob. 8.4ECh. 2.8 - Prob. 8.5ECh. 2.8 - Prob. 8.6ECh. 2.8 - Prob. 8.7ECh. 2.8 - Prob. 8.8ECh. 2.8 - Prob. 8.9ECh. 2.8 - Prob. 8.10E
Ch. 2.8 - Prob. 8.11ECh. 2.8 - Prob. 8.12ECh. 2.8 - Prob. 8.13ECh. 2.8 - Prob. 8.14ECh. 2.8 - Prob. 8.15ECh. 2.8 - Prob. 8.16ECh. 2.8 - Prob. 8.17ECh. 2.8 - Prob. 8.18ECh. 2.8 - Prob. 8.19ECh. 2.9 - Prob. 9.1ECh. 2.9 - Prob. 9.2ECh. 2.9 - Prob. 9.3ECh. 2.9 - Prob. 9.4ECh. 2.9 - Prob. 9.5ECh. 2.9 - Prob. 9.6ECh. 2.9 - Prob. 9.7ECh. 2.9 - Prob. 9.8ECh. 2.9 - Prob. 9.9ECh. 2.9 - Prob. 9.10ECh. 2.9 - Prob. 9.11ECh. 2.9 - Prob. 9.12ECh. 2.9 - Prob. 9.13ECh. 2.9 - Prob. 9.14ECh. 2.9 - Prob. 9.15ECh. 2.9 - Prob. 9.16ECh. 2.9 - Prob. 9.17ECh. 2.9 - Prob. 9.18ECh. 2.10 - Prob. 10.1ECh. 2.10 - Prob. 10.2ECh. 2.10 - Prob. 10.3ECh. 2.10 - Prob. 10.4ECh. 2.10 - Prob. 10.5ECh. 2.10 - Prob. 10.6ECh. 2.10 - Prob. 10.7ECh. 2.10 - Prob. 10.8ECh. 2.10 - Prob. 10.9ECh. 2.10 - Let A=x:4x and let B=x:2x. Prove that AB.Ch. 2.10 - Prob. 10.11ECh. 2.10 - Prob. 10.12ECh. 2.10 - Prob. 10.13ECh. 2.10 - Prob. 10.14ECh. 2.10 - Prob. 10.15ECh. 2.11 - Write the following sentences using the quantifier...Ch. 2.11 - Prob. 11.2ECh. 2.11 - Prob. 11.3ECh. 2.11 - Prob. 11.4ECh. 2.11 - Prob. 11.5ECh. 2.11 - Prob. 11.6ECh. 2.11 - Prob. 11.7ECh. 2.11 - Prob. 11.8ECh. 2.12 - Prob. 12.1ECh. 2.12 - Prob. 12.2ECh. 2.12 - Prob. 12.3ECh. 2.12 - Prob. 12.4ECh. 2.12 - Prob. 12.5ECh. 2.12 - Prob. 12.6ECh. 2.12 - Prob. 12.7ECh. 2.12 - Prob. 12.8ECh. 2.12 - Prob. 12.9ECh. 2.12 - Prob. 12.10ECh. 2.12 - Prob. 12.11ECh. 2.12 - Prob. 12.12ECh. 2.12 - Prob. 12.13ECh. 2.12 - Prob. 12.14ECh. 2.12 - Prob. 12.15ECh. 2.12 - Prob. 12.16ECh. 2.12 - Prob. 12.17ECh. 2.12 - Prob. 12.18ECh. 2.12 - Prob. 12.19ECh. 2.12 - Prob. 12.20ECh. 2.12 - Prob. 12.21ECh. 2.12 - Prob. 12.22ECh. 2.12 - Prob. 12.23ECh. 2.12 - Prob. 12.24ECh. 2.12 - Prob. 12.25ECh. 2.12 - Prob. 12.26ECh. 2.12 - Prob. 12.27ECh. 2.12 - Prob. 12.28ECh. 2.12 - Prob. 12.29ECh. 2.12 - Prob. 12.30ECh. 2.13 - Prob. 13.1ECh. 2.13 - Prob. 13.2ECh. 2.13 - Prob. 13.3ECh. 2.13 - Prob. 13.4ECh. 2.13 - Prob. 13.5ECh. 2.13 - Prob. 13.6ECh. 2.13 - Prob. 13.7ECh. 2 - Prob. 1STCh. 2 - Prob. 2STCh. 2 - Prob. 3STCh. 2 - Prob. 4STCh. 2 - Prob. 5STCh. 2 - Prob. 6STCh. 2 - Prob. 7STCh. 2 - Prob. 8STCh. 2 - Prob. 9STCh. 2 - Prob. 10STCh. 2 - Prob. 11STCh. 2 - Prob. 12STCh. 2 - Prob. 13STCh. 2 - Prob. 14STCh. 2 - Prob. 15STCh. 2 - Prob. 16STCh. 2 - Prob. 17STCh. 2 - Prob. 18STCh. 2 - Prob. 19STCh. 2 - Prob. 20ST
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- 1 (Expected Shortfall) Suppose the price of an asset Pt follows a normal random walk, i.e., Pt = Po+r₁ + ... + rt with r₁, r2,... being IID N(μ, o²). Po+r1+. ⚫ Suppose the VaR of rt is VaRq(rt) at level q, find the VaR of the price in T days, i.e., VaRq(Pt – Pt–T). - • If ESq(rt) = A, find ES₁(Pt – Pt–T).arrow_forward2 (Normal Distribution) Let rt be a log return. Suppose that r₁, 2, ... are IID N(0.06, 0.47). What is the distribution of rt (4) = rt + rt-1 + rt-2 + rt-3? What is P(rt (4) < 2)? What is the covariance between r2(2) = 1 + 12 and 13(2) = r² + 13? • What is the conditional distribution of r₁(3) = rt + rt-1 + rt-2 given rt-2 = 0.6?arrow_forward3 (Sharpe-ratio) Suppose that X1, X2,..., is a lognormal geometric random walk with parameters (μ, o²). Specifically, suppose that X = Xo exp(rı + ...Tk), where Xo is a fixed constant and r1, T2, ... are IID N(μ, o²). Find the Sharpe-ratios of rk and log(Xk) — log(Xo) respectively, assuming the risk free return is 0.arrow_forward
- 4 (Value-at-Risk and Expected Shortfall) Suppose X Find VaR0.02(X) and ES0.02 (X). ~ Uniform(-1, 1).arrow_forward亚 ח Variables Name avgdr employ educ exerany Label AVG ALCOHOLIC DRINKS PER DAY IN PAST 30 EMPLOYMENT STATUS EDUCATION LEVEL EXERCISE IN PAST 30 DAYSarrow_forwardNumerical anaarrow_forward
- Variables Name wage hours IQ KWW educ exper tenure age married black south urban sibs brthord meduc feduc Label monthly earnings average weekly hours IQ score knowledge of world work score years of education years of work experience years with current employer age in years =1 if married =1 if black =1 if live in south =1 if live in SMSA number of siblings birth order mother's education father's educationarrow_forwardInformation for questions 4 • • Please Download "wages" from Canvas (the link to this dataset is right below the HWA1 questions - it is a Microsoft excel worksheet) and store it in your favorite folder. It contains 797 observations and 16 variables. The "state" variable gives the names of the states involved in this dataset. • You need to have excel on your computer to open this dataset. i. You should use File > Import > Excel Spreadsheet etc. as done in class 3 convert this file into a Stata dataset. Once you are done, write the final STATA code that makes the transformation of an excel file to a STATA file possible. ii. Write a code that will close the log file that has been open since Question 1 part ii.arrow_forwardThe mean, variance, skewness and kurtosis of a dataset are given as - Mean = 15, Variance = 20, SKewness = 1.5 and Kurtosis = 3.5 calculate the first four raw moments. (Note- Please include as much detailed solution/steps in the solution to understand, Thank you!)arrow_forward
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